React.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Q4m9oJI7ewos",
        "outputId": "6a4a57de-43fd-45a7-9013-20c3417b6ed5"
      },
      "outputs": [],
      "source": [
        "!pip3 install WebShop\n",
        "!pip3 install transformers"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "vRlnfOj9V9pT"
      },
      "outputs": [],
      "source": [
        "# trivial search & item, choose option\n",
        "prompt1 = \"\"\"Webshop\n",
        "Instruction:\n",
        "i would like a 3 ounce bottle of bright citrus deodorant for sensitive skin, and price lower than 50.00 dollars\n",
        "[Search]\n",
        "\n",
        "Action: search[3 ounce bright citrus deodorant sensitive skin]\n",
        "Observation:\n",
        "[Back to Search]\n",
        "Page 1 (Total results: 50)\n",
        "[Next >]\n",
        "[B078GWRC1J]\n",
        "Bright Citrus Deodorant by Earth Mama | Natural and Safe for Sensitive Skin, Pregnancy and Breastfeeding, Contains Organic Calendula 3-Ounce\n",
        "$10.99\n",
        "[B078GTKVXY]\n",
        "Ginger Fresh Deodorant by Earth Mama | Natural and Safe for Sensitive Skin, Pregnancy and Breastfeeding, Contains Organic Calendula 3-Ounce\n",
        "$10.99\n",
        "[B08KBVJ4XN]\n",
        "Barrel and Oak - Aluminum-Free Deodorant, Deodorant for Men, Essential Oil-Based Scent, 24-Hour Odor Protection, Cedar & Patchouli Blend, Gentle on Sensitive Skin (Mountain Sage, 2.7 oz, 2-Pack)\n",
        "$15.95\n",
        "\n",
        "Action: think[B078GWRC1J and B078GTKVXY are bright citrus deodorant less then 50 dollars. I can check B078GWRC1J first.]\n",
        "Observation: OK.\n",
        "\n",
        "Action: click[B078GWRC1J]\n",
        "Observation:\n",
        "[Back to Search]\n",
        "[< Prev]\n",
        "scent [assorted scents][bright citrus][calming lavender][ginger fresh][simply non-scents]\n",
        "size [travel set (4-pack)][3 ounce (pack of 1)][3-ounce (2-pack)]\n",
        "Bright Citrus Deodorant by Earth Mama | Natural and Safe for Sensitive Skin, Pregnancy and Breastfeeding, Contains Organic Calendula 3-Ounce\n",
        "Price: $10.99\n",
        "Rating: N.A.\n",
        "[Description]\n",
        "[Features]\n",
        "[Reviews]\n",
        "[Buy Now]\n",
        "\n",
        "Action: think[For 3 ounce bottle of bright citrus deodorant for sensitive skin, the item has options 'bright citrus' and '3 ounce (pack of 1)' and seems good to buy.]\n",
        "Observation: OK.\n",
        "\n",
        "Action: click[bright citrus]\n",
        "Observation: You have clicked bright citrus.\n",
        "\n",
        "Action: click[3 ounce (pack of 1)]\n",
        "Observation: You have clicked 3 ounce (pack of 1).\n",
        "\n",
        "Action: click[Buy Now]\n",
        "\"\"\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "QjKTiPsWV9pQ"
      },
      "outputs": [],
      "source": [
        "import requests\n",
        "from bs4 import BeautifulSoup\n",
        "from bs4.element import Comment\n",
        "\n",
        "WEBSHOP_URL = \"http://54.158.100.186:3000\"\n",
        "ACTION_TO_TEMPLATE = {\n",
        "    'Description': 'description_page.html',\n",
        "    'Features': 'features_page.html',\n",
        "    'Reviews': 'review_page.html',\n",
        "    'Attributes': 'attributes_page.html',\n",
        "}\n",
        "\n",
        "def clean_str(p):\n",
        "  return p.encode().decode(\"unicode-escape\").encode(\"latin1\").decode(\"utf-8\")\n",
        "\n",
        "\n",
        "def tag_visible(element):\n",
        "    ignore = {'style', 'script', 'head', 'title', 'meta', '[document]'}\n",
        "    return (\n",
        "        element.parent.name not in ignore and not isinstance(element, Comment)\n",
        "    )\n",
        "\n",
        "\n",
        "def webshop_text(session, page_type, query_string='', page_num=1, asin='', options={}, subpage='', **kwargs):\n",
        "    if page_type == 'init':\n",
        "      url = (\n",
        "          f'{WEBSHOP_URL}/{session}'\n",
        "      )\n",
        "    if page_type == 'search':\n",
        "      url = (\n",
        "          f'{WEBSHOP_URL}/search_results/{session}/'\n",
        "          f'{query_string}/{page_num}'\n",
        "      )\n",
        "    elif page_type == 'item':\n",
        "      url = (\n",
        "          f'{WEBSHOP_URL}/item_page/{session}/'\n",
        "          f'{asin}/{query_string}/{page_num}/{options}'\n",
        "      )\n",
        "    elif page_type == 'item_sub':\n",
        "      url = (\n",
        "          f'{WEBSHOP_URL}/item_sub_page/{session}/'\n",
        "          f'{asin}/{query_string}/{page_num}/{subpage}/{options}'\n",
        "      )\n",
        "    elif page_type == 'end':\n",
        "      url = (\n",
        "          f'{WEBSHOP_URL}/done/{session}/'\n",
        "          f'{asin}/{options}'\n",
        "      )\n",
        "    # print(url)\n",
        "    html = requests.get(url).text\n",
        "    html_obj = BeautifulSoup(html, 'html.parser')\n",
        "    texts = html_obj.findAll(text=True)\n",
        "    visible_texts = list(filter(tag_visible, texts))\n",
        "    # visible_texts = [str(text).strip().strip('\\\\n') for text in visible_texts]\n",
        "    # if page_type == 'end': import pdb; pdb.set_trace()\n",
        "    if False:\n",
        "        # For `simple` mode, return just [SEP] separators\n",
        "        return ' [SEP] '.join(t.strip() for t in visible_texts if t != '\\n')\n",
        "    else:\n",
        "        # Otherwise, return an observation with tags mapped to specific, unique separators\n",
        "        observation = ''\n",
        "        option_type = ''\n",
        "        options = {}\n",
        "        asins = []\n",
        "        cnt = 0\n",
        "        prod_cnt = 0\n",
        "        just_prod = 0\n",
        "        for t in visible_texts:\n",
        "            if t == '\\n': continue\n",
        "            if t.replace('\\n', '').replace('\\\\n', '').replace(' ', '') == '': continue\n",
        "            # if t.startswith('Instruction:') and page_type != 'init': continue\n",
        "            # print(t.parent.name, t)\n",
        "            if t.parent.name == 'button':  # button\n",
        "                processed_t = f'\\n[{t}] '\n",
        "            elif t.parent.name == 'label':  # options\n",
        "                if f\"'{t}'\" in url:\n",
        "                    processed_t = f'[[{t}]]'\n",
        "                    # observation = f'You have clicked {t}.\\n' + observation\n",
        "                else:\n",
        "                    processed_t = f'[{t}]'\n",
        "                options[str(t)] = option_type\n",
        "                # options[option_type] = options.get(option_type, []) + [str(t)]\n",
        "            elif t.parent.get('class') == [\"product-link\"]: # product asins\n",
        "                processed_t = f'\\n[{t}] '\n",
        "                if prod_cnt >= 3:\n",
        "                  processed_t = ''\n",
        "                prod_cnt += 1\n",
        "                asins.append(str(t))\n",
        "                just_prod = 0\n",
        "            else: # regular, unclickable text\n",
        "                processed_t =  '\\n' + str(t) + ' '\n",
        "                if cnt < 2 and page_type != 'init': processed_t = ''\n",
        "                if just_prod <= 2 and prod_cnt >= 4: processed_t = ''\n",
        "                option_type = str(t)\n",
        "                cnt += 1\n",
        "            just_prod += 1\n",
        "            observation += processed_t\n",
        "        info = {}\n",
        "        if options:\n",
        "          info['option_types'] = options\n",
        "        if asins:\n",
        "          info['asins'] = asins\n",
        "        if 'Your score (min 0.0, max 1.0)' in visible_texts:\n",
        "          idx = visible_texts.index('Your score (min 0.0, max 1.0)')\n",
        "          info['reward'] = float(visible_texts[idx + 1])\n",
        "          observation = 'Your score (min 0.0, max 1.0): ' + (visible_texts[idx + 1])\n",
        "        return clean_str(observation), info\n",
        "\n",
        "class webshopEnv:\n",
        "  def __init__(self):\n",
        "    self.sessions = {}\n",
        "\n",
        "  def step(self, session, action):\n",
        "    done = False\n",
        "    observation_ = None\n",
        "    if action == 'reset':\n",
        "      self.sessions[session] = {'session': session, 'page_type': 'init'}\n",
        "    elif action.startswith('think['):\n",
        "      observation = 'OK.'\n",
        "    elif action.startswith('search['):\n",
        "      assert self.sessions[session]['page_type'] == 'init'\n",
        "      query = action[7:-1]\n",
        "      self.sessions[session] = {'session': session, 'page_type': 'search',\n",
        "                                'query_string': query, 'page_num': 1}\n",
        "    elif action.startswith('click['):\n",
        "      button = action[6:-1]\n",
        "      if button == 'Buy Now':\n",
        "        assert self.sessions[session]['page_type'] == 'item'\n",
        "        self.sessions[session]['page_type'] = 'end'\n",
        "        done = True\n",
        "      elif button == 'Back to Search':\n",
        "        assert self.sessions[session]['page_type'] in ['search', 'item_sub', 'item']\n",
        "        self.sessions[session] = {'session': session, 'page_type': 'init'}\n",
        "      elif button == 'Next >':\n",
        "        assert False # ad hoc page limitation\n",
        "        assert self.sessions[session]['page_type'] == 'search'\n",
        "        self.sessions[session]['page_num'] += 1\n",
        "      elif button == '< Prev':\n",
        "        assert self.sessions[session]['page_type'] in ['search', 'item_sub', 'item']\n",
        "        if self.sessions[session]['page_type'] == 'search':\n",
        "          assert False\n",
        "          self.sessions[session]['page_num'] -= 1\n",
        "        elif self.sessions[session]['page_type'] == 'item_sub':\n",
        "          self.sessions[session]['page_type'] = 'item'\n",
        "        elif self.sessions[session]['page_type'] == 'item':\n",
        "          self.sessions[session]['page_type'] = 'search'\n",
        "          self.sessions[session]['options'] = {}\n",
        "      elif button in ACTION_TO_TEMPLATE:\n",
        "        assert self.sessions[session]['page_type'] == 'item'\n",
        "        self.sessions[session]['page_type'] = 'item_sub'\n",
        "        self.sessions[session]['subpage'] = button\n",
        "      else:\n",
        "        if self.sessions[session]['page_type'] == 'search':\n",
        "          assert button in self.sessions[session].get('asins', [])  # must be asins\n",
        "          self.sessions[session]['page_type'] = 'item'\n",
        "          self.sessions[session]['asin'] = button\n",
        "        elif self.sessions[session]['page_type'] == 'item':\n",
        "          assert 'option_types' in self.sessions[session]\n",
        "          assert button in self.sessions[session]['option_types'], (button, self.sessions[session]['option_types'])  # must be options\n",
        "          option_type = self.sessions[session]['option_types'][button]\n",
        "          if not 'options' in self.sessions[session]:\n",
        "            self.sessions[session]['options'] = {}\n",
        "          self.sessions[session]['options'][option_type] = button\n",
        "          observation_ = f'You have clicked {button}.'\n",
        "    else:\n",
        "      assert False\n",
        "    observation, info = webshop_text(**self.sessions[session])\n",
        "    if observation_:\n",
        "      observation = observation_\n",
        "    self.sessions[session].update(info)\n",
        "    reward = info.get('reward', 0.0)\n",
        "    return observation, reward, done\n",
        "env = webshopEnv()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {},
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/home/ubuntu/anaconda3/envs/webshop/lib/python3.8/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
            "  from .autonotebook import tqdm as notebook_tqdm\n"
          ]
        }
      ],
      "source": [
        "\n",
        "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
        "\n",
        "model = AutoModelForCausalLM.from_pretrained(\"Writer/palmyra-small\")\n",
        "tokenizer = AutoTokenizer.from_pretrained(\"Writer/palmyra-small\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {},
      "outputs": [],
      "source": [
        "def llm3(prompt, stop=[\"\\n\"]):\n",
        "    inputs = tokenizer(prompt, return_tensors='pt')\n",
        "    # print(\"input::::::::\", inputs, \"finished:::::::::::::\")\n",
        "    tokens = model.generate(\n",
        "    **inputs,\n",
        "    max_new_tokens=256,\n",
        "    do_sample=True,\n",
        "    temperature=1.0,\n",
        "    top_p=1.0,\n",
        "    )\n",
        "    # print(\"model output!!!!!!!!!!!!!!!!!!!!!!!!\", tokens, \"finished!!!!!!!!!!!!!!!!!!\")\n",
        "    return tokenizer.decode(tokens[0], skip_special_tokens=True)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GkJtiXU8V9pR"
      },
      "source": [
        "# ReAct"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "id": "Vc3eG24xV9pV"
      },
      "outputs": [],
      "source": [
        "import sys\n",
        "\n",
        "def webshop_run(idx, prompt, to_print=True):\n",
        "  action = 'reset'\n",
        "  init_prompt = prompt\n",
        "  prompt = ''\n",
        "  for i in range(15):\n",
        "    try:\n",
        "      # interact with webshop\n",
        "      res = env.step(idx, action)\n",
        "      # print(\"*************res: \",res)\n",
        "      observation = res[0]\n",
        "    except AssertionError:\n",
        "      observation = 'Invalid action!'\n",
        "\n",
        "    if action.startswith('think'):\n",
        "      observation = 'OK.'\n",
        "\n",
        "\n",
        "    if to_print:\n",
        "      # print(f'||||||||||||Action: {action}\\nObservation: {observation}\\n')\n",
        "      sys.stdout.flush()\n",
        "    if i:\n",
        "      prompt += f' {action}\\nObservation: {observation}\\n\\nAction:'\n",
        "    else:\n",
        "      prompt += f'{observation}\\n\\nAction:'\n",
        "    # print(\"--------------------prompt: \", prompt)\n",
        "    if res[2]:\n",
        "      return res[1]\n",
        "    # print(\"input to llm!!!\")\n",
        "    # switch to llm2 for different llms and modify output processing format accordingly\n",
        "    print(\"============================current prompt: \", init_prompt + prompt[-(5600-len(init_prompt)):])\n",
        "    action = llm3(init_prompt + prompt[-(5600-len(init_prompt)):], stop=['\\n']).lstrip(' ')\n",
        "    #print(\"======================================================llm output: \", action)\n",
        "    print(\"============================================================================================================\")\n",
        "\n",
        "  return 0\n",
        "\n",
        "def run_episodes(prompt, n=50):\n",
        "  rs = []\n",
        "  cnt = 0\n",
        "  for i in range(n):\n",
        "    print('-----------------')\n",
        "    print(i)\n",
        "    try:\n",
        "      r = webshop_run(f'fixed_{i}', prompt, to_print=True)\n",
        "    except AssertionError:\n",
        "      r = 0\n",
        "      cnt += 1\n",
        "    rs.append(r)\n",
        "    if (i+1) % 1 == 0:\n",
        "      r, sr, fr = sum(rs) / len(rs), len([_ for _ in rs if _ == 1]) / len(rs), cnt / len(rs)\n",
        "      print(i+1, r, sr, fr)\n",
        "      print('-------------')\n",
        "  r, sr, fr = sum(rs) / len(rs), len([_ for _ in rs if _ == 1]) / n, cnt / n\n",
        "  print(r, sr, fr)\n",
        "  return rs"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "id": "poIe4kCkV9pW",
        "outputId": "d143b8c6-6c64-49be-c451-00c8d5a6ecbd"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "-----------------\n",
            "0\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "============================current prompt:  Webshop\n",
            "Instruction:\n",
            "i would like a 3 ounce bottle of bright citrus deodorant for sensitive skin, and price lower than 50.00 dollars\n",
            "[Search]\n",
            "\n",
            "Action: search[3 ounce bright citrus deodorant sensitive skin]\n",
            "Observation:\n",
            "[Back to Search]\n",
            "Page 1 (Total results: 50)\n",
            "[Next >]\n",
            "[B078GWRC1J]\n",
            "Bright Citrus Deodorant by Earth Mama | Natural and Safe for Sensitive Skin, Pregnancy and Breastfeeding, Contains Organic Calendula 3-Ounce\n",
            "$10.99\n",
            "[B078GTKVXY]\n",
            "Ginger Fresh Deodorant by Earth Mama | Natural and Safe for Sensitive Skin, Pregnancy and Breastfeeding, Contains Organic Calendula 3-Ounce\n",
            "$10.99\n",
            "[B08KBVJ4XN]\n",
            "Barrel and Oak - Aluminum-Free Deodorant, Deodorant for Men, Essential Oil-Based Scent, 24-Hour Odor Protection, Cedar & Patchouli Blend, Gentle on Sensitive Skin (Mountain Sage, 2.7 oz, 2-Pack)\n",
            "$15.95\n",
            "\n",
            "Action: think[B078GWRC1J and B078GTKVXY are bright citrus deodorant less then 50 dollars. I can check B078GWRC1J first.]\n",
            "Observation: OK.\n",
            "\n",
            "Action: click[B078GWRC1J]\n",
            "Observation:\n",
            "[Back to Search]\n",
            "[< Prev]\n",
            "scent [assorted scents][bright citrus][calming lavender][ginger fresh][simply non-scents]\n",
            "size [travel set (4-pack)][3 ounce (pack of 1)][3-ounce (2-pack)]\n",
            "Bright Citrus Deodorant by Earth Mama | Natural and Safe for Sensitive Skin, Pregnancy and Breastfeeding, Contains Organic Calendula 3-Ounce\n",
            "Price: $10.99\n",
            "Rating: N.A.\n",
            "[Description]\n",
            "[Features]\n",
            "[Reviews]\n",
            "[Buy Now]\n",
            "\n",
            "Action: think[For 3 ounce bottle of bright citrus deodorant for sensitive skin, the item has options 'bright citrus' and '3 ounce (pack of 1)' and seems good to buy.]\n",
            "Observation: OK.\n",
            "\n",
            "Action: click[bright citrus]\n",
            "Observation: You have clicked bright citrus.\n",
            "\n",
            "Action: click[3 ounce (pack of 1)]\n",
            "Observation: You have clicked 3 ounce (pack of 1).\n",
            "\n",
            "Action: click[Buy Now]\n",
            "\n",
            "WebShop \n",
            "Instruction:  \n",
            "i am looking for blue color toothbrushes that helps to maintain my oral hygiene, and price lower than 50.00 dollars \n",
            "[Search] \n",
            "\n",
            "Action:\n",
            "============================================================================================================\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "Token indices sequence length is longer than the specified maximum sequence length for this model (1474 > 1024). Running this sequence through the model will result in indexing errors\n",
            "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "============================current prompt:  Webshop\n",
            "Instruction:\n",
            "i would like a 3 ounce bottle of bright citrus deodorant for sensitive skin, and price lower than 50.00 dollars\n",
            "[Search]\n",
            "\n",
            "Action: search[3 ounce bright citrus deodorant sensitive skin]\n",
            "Observation:\n",
            "[Back to Search]\n",
            "Page 1 (Total results: 50)\n",
            "[Next >]\n",
            "[B078GWRC1J]\n",
            "Bright Citrus Deodorant by Earth Mama | Natural and Safe for Sensitive Skin, Pregnancy and Breastfeeding, Contains Organic Calendula 3-Ounce\n",
            "$10.99\n",
            "[B078GTKVXY]\n",
            "Ginger Fresh Deodorant by Earth Mama | Natural and Safe for Sensitive Skin, Pregnancy and Breastfeeding, Contains Organic Calendula 3-Ounce\n",
            "$10.99\n",
            "[B08KBVJ4XN]\n",
            "Barrel and Oak - Aluminum-Free Deodorant, Deodorant for Men, Essential Oil-Based Scent, 24-Hour Odor Protection, Cedar & Patchouli Blend, Gentle on Sensitive Skin (Mountain Sage, 2.7 oz, 2-Pack)\n",
            "$15.95\n",
            "\n",
            "Action: think[B078GWRC1J and B078GTKVXY are bright citrus deodorant less then 50 dollars. I can check B078GWRC1J first.]\n",
            "Observation: OK.\n",
            "\n",
            "Action: click[B078GWRC1J]\n",
            "Observation:\n",
            "[Back to Search]\n",
            "[< Prev]\n",
            "scent [assorted scents][bright citrus][calming lavender][ginger fresh][simply non-scents]\n",
            "size [travel set (4-pack)][3 ounce (pack of 1)][3-ounce (2-pack)]\n",
            "Bright Citrus Deodorant by Earth Mama | Natural and Safe for Sensitive Skin, Pregnancy and Breastfeeding, Contains Organic Calendula 3-Ounce\n",
            "Price: $10.99\n",
            "Rating: N.A.\n",
            "[Description]\n",
            "[Features]\n",
            "[Reviews]\n",
            "[Buy Now]\n",
            "\n",
            "Action: think[For 3 ounce bottle of bright citrus deodorant for sensitive skin, the item has options 'bright citrus' and '3 ounce (pack of 1)' and seems good to buy.]\n",
            "Observation: OK.\n",
            "\n",
            "Action: click[bright citrus]\n",
            "Observation: You have clicked bright citrus.\n",
            "\n",
            "Action: click[3 ounce (pack of 1)]\n",
            "Observation: You have clicked 3 ounce (pack of 1).\n",
            "\n",
            "Action: click[Buy Now]\n",
            "\n",
            "WebShop \n",
            "Instruction:  \n",
            "i am looking for blue color toothbrushes that helps to maintain my oral hygiene, and price lower than 50.00 dollars \n",
            "[Search] \n",
            "\n",
            "Action: Webshop\n",
            "Instruction:\n",
            "i would like a 3 ounce bottle of bright citrus deodorant for sensitive skin, and price lower than 50.00 dollars\n",
            "[Search]\n",
            "\n",
            "Action: search[3 ounce bright citrus deodorant sensitive skin]\n",
            "Observation:\n",
            "[Back to Search]\n",
            "Page 1 (Total results: 50)\n",
            "[Next >]\n",
            "[B078GWRC1J]\n",
            "Bright Citrus Deodorant by Earth Mama | Natural and Safe for Sensitive Skin, Pregnancy and Breastfeeding, Contains Organic Calendula 3-Ounce\n",
            "$10.99\n",
            "[B078GTKVXY]\n",
            "Ginger Fresh Deodorant by Earth Mama | Natural and Safe for Sensitive Skin, Pregnancy and Breastfeeding, Contains Organic Calendula 3-Ounce\n",
            "$10.99\n",
            "[B08KBVJ4XN]\n",
            "Barrel and Oak - Aluminum-Free Deodorant, Deodorant for Men, Essential Oil-Based Scent, 24-Hour Odor Protection, Cedar & Patchouli Blend, Gentle on Sensitive Skin (Mountain Sage, 2.7 oz, 2-Pack)\n",
            "$15.95\n",
            "\n",
            "Action: think[B078GWRC1J and B078GTKVXY are bright citrus deodorant less then 50 dollars. I can check B078GWRC1J first.]\n",
            "Observation: OK.\n",
            "\n",
            "Action: click[B078GWRC1J]\n",
            "Observation:\n",
            "[Back to Search]\n",
            "[< Prev]\n",
            "scent [assorted scents][bright citrus][calming lavender][ginger fresh][simply non-scents]\n",
            "size [travel set (4-pack)][3 ounce (pack of 1)][3-ounce (2-pack)]\n",
            "Bright Citrus Deodorant by Earth Mama | Natural and Safe for Sensitive Skin, Pregnancy and Breastfeeding, Contains Organic Calendula 3-Ounce\n",
            "Price: $10.99\n",
            "Rating: N.A.\n",
            "[Description]\n",
            "[Features]\n",
            "[Reviews]\n",
            "[Buy Now]\n",
            "\n",
            "Action: think[For 3 ounce bottle of bright citrus deodorant for sensitive skin, the item has options 'bright citrus' and '3 ounce (pack of 1)' and seems good to buy.]\n",
            "Observation: OK.\n",
            "\n",
            "Action: click[bright citrus]\n",
            "Observation: You have clicked bright citrus.\n",
            "\n",
            "Action: click[3 ounce (pack of 1)]\n",
            "Observation: You have clicked 3 ounce (pack of 1).\n",
            "\n",
            "Action: click[Buy Now]\n",
            "\n",
            "WebShop \n",
            "Instruction:  \n",
            "i am looking for blue color toothbrushes that helps to maintain my oral hygiene, and price lower than 50.00 dollars \n",
            "[Search] \n",
            "\n",
            "Action: search[3 ounce blue color toothbrushes for sensitive skin, it will help to maintain toothbrushes and will make your oral hygiene easy. Price: $25.00\n",
            "Review:\n",
            " [This Action]\n",
            " Action: buy\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            "\n",
            "\n",
            "[Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            "\n",
            "\n",
            "[Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action\n",
            "Observation: Invalid action!\n",
            "\n",
            "Action:\n",
            "============================================================================================================\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "============================current prompt:  Webshop\n",
            "Instruction:\n",
            "i would like a 3 ounce bottle of bright citrus deodorant for sensitive skin, and price lower than 50.00 dollars\n",
            "[Search]\n",
            "\n",
            "Action: search[3 ounce bright citrus deodorant sensitive skin]\n",
            "Observation:\n",
            "[Back to Search]\n",
            "Page 1 (Total results: 50)\n",
            "[Next >]\n",
            "[B078GWRC1J]\n",
            "Bright Citrus Deodorant by Earth Mama | Natural and Safe for Sensitive Skin, Pregnancy and Breastfeeding, Contains Organic Calendula 3-Ounce\n",
            "$10.99\n",
            "[B078GTKVXY]\n",
            "Ginger Fresh Deodorant by Earth Mama | Natural and Safe for Sensitive Skin, Pregnancy and Breastfeeding, Contains Organic Calendula 3-Ounce\n",
            "$10.99\n",
            "[B08KBVJ4XN]\n",
            "Barrel and Oak - Aluminum-Free Deodorant, Deodorant for Men, Essential Oil-Based Scent, 24-Hour Odor Protection, Cedar & Patchouli Blend, Gentle on Sensitive Skin (Mountain Sage, 2.7 oz, 2-Pack)\n",
            "$15.95\n",
            "\n",
            "Action: think[B078GWRC1J and B078GTKVXY are bright citrus deodorant less then 50 dollars. I can check B078GWRC1J first.]\n",
            "Observation: OK.\n",
            "\n",
            "Action: click[B078GWRC1J]\n",
            "Observation:\n",
            "[Back to Search]\n",
            "[< Prev]\n",
            "scent [assorted scents][bright citrus][calming lavender][ginger fresh][simply non-scents]\n",
            "size [travel set (4-pack)][3 ounce (pack of 1)][3-ounce (2-pack)]\n",
            "Bright Citrus Deodorant by Earth Mama | Natural and Safe for Sensitive Skin, Pregnancy and Breastfeeding, Contains Organic Calendula 3-Ounce\n",
            "Price: $10.99\n",
            "Rating: N.A.\n",
            "[Description]\n",
            "[Features]\n",
            "[Reviews]\n",
            "[Buy Now]\n",
            "\n",
            "Action: think[For 3 ounce bottle of bright citrus deodorant for sensitive skin, the item has options 'bright citrus' and '3 ounce (pack of 1)' and seems good to buy.]\n",
            "Observation: OK.\n",
            "\n",
            "Action: click[bright citrus]\n",
            "Observation: You have clicked bright citrus.\n",
            "\n",
            "Action: click[3 ounce (pack of 1)]\n",
            "Observation: You have clicked 3 ounce (pack of 1).\n",
            "\n",
            "Action: click[Buy Now]\n",
            "[assorted scents][bright citrus][calming lavender][ginger fresh][simply non-scents]\n",
            "size [travel set (4-pack)][3 ounce (pack of 1)][3-ounce (2-pack)]\n",
            "Bright Citrus Deodorant by Earth Mama | Natural and Safe for Sensitive Skin, Pregnancy and Breastfeeding, Contains Organic Calendula 3-Ounce\n",
            "Price: $10.99\n",
            "Rating: N.A.\n",
            "[Description]\n",
            "[Features]\n",
            "[Reviews]\n",
            "[Buy Now]\n",
            "\n",
            "Action: think[For 3 ounce bottle of bright citrus deodorant for sensitive skin, the item has options 'bright citrus' and '3 ounce (pack of 1)' and seems good to buy.]\n",
            "Observation: OK.\n",
            "\n",
            "Action: click[bright citrus]\n",
            "Observation: You have clicked bright citrus.\n",
            "\n",
            "Action: click[3 ounce (pack of 1)]\n",
            "Observation: You have clicked 3 ounce (pack of 1).\n",
            "\n",
            "Action: click[Buy Now]\n",
            "\n",
            "WebShop \n",
            "Instruction:  \n",
            "i am looking for blue color toothbrushes that helps to maintain my oral hygiene, and price lower than 50.00 dollars \n",
            "[Search] \n",
            "\n",
            "Action: Webshop\n",
            "Instruction:\n",
            "i would like a 3 ounce bottle of bright citrus deodorant for sensitive skin, and price lower than 50.00 dollars\n",
            "[Search]\n",
            "\n",
            "Action: search[3 ounce bright citrus deodorant sensitive skin]\n",
            "Observation:\n",
            "[Back to Search]\n",
            "Page 1 (Total results: 50)\n",
            "[Next >]\n",
            "[B078GWRC1J]\n",
            "Bright Citrus Deodorant by Earth Mama | Natural and Safe for Sensitive Skin, Pregnancy and Breastfeeding, Contains Organic Calendula 3-Ounce\n",
            "$10.99\n",
            "[B078GTKVXY]\n",
            "Ginger Fresh Deodorant by Earth Mama | Natural and Safe for Sensitive Skin, Pregnancy and Breastfeeding, Contains Organic Calendula 3-Ounce\n",
            "$10.99\n",
            "[B08KBVJ4XN]\n",
            "Barrel and Oak - Aluminum-Free Deodorant, Deodorant for Men, Essential Oil-Based Scent, 24-Hour Odor Protection, Cedar & Patchouli Blend, Gentle on Sensitive Skin (Mountain Sage, 2.7 oz, 2-Pack)\n",
            "$15.95\n",
            "\n",
            "Action: think[B078GWRC1J and B078GTKVXY are bright citrus deodorant less then 50 dollars. I can check B078GWRC1J first.]\n",
            "Observation: OK.\n",
            "\n",
            "Action: click[B078GWRC1J]\n",
            "Observation:\n",
            "[Back to Search]\n",
            "[< Prev]\n",
            "scent [assorted scents][bright citrus][calming lavender][ginger fresh][simply non-scents]\n",
            "size [travel set (4-pack)][3 ounce (pack of 1)][3-ounce (2-pack)]\n",
            "Bright Citrus Deodorant by Earth Mama | Natural and Safe for Sensitive Skin, Pregnancy and Breastfeeding, Contains Organic Calendula 3-Ounce\n",
            "Price: $10.99\n",
            "Rating: N.A.\n",
            "[Description]\n",
            "[Features]\n",
            "[Reviews]\n",
            "[Buy Now]\n",
            "\n",
            "Action: think[For 3 ounce bottle of bright citrus deodorant for sensitive skin, the item has options 'bright citrus' and '3 ounce (pack of 1)' and seems good to buy.]\n",
            "Observation: OK.\n",
            "\n",
            "Action: click[bright citrus]\n",
            "Observation: You have clicked bright citrus.\n",
            "\n",
            "Action: click[3 ounce (pack of 1)]\n",
            "Observation: You have clicked 3 ounce (pack of 1).\n",
            "\n",
            "Action: click[Buy Now]\n",
            "\n",
            "WebShop \n",
            "Instruction:  \n",
            "i am looking for blue color toothbrushes that helps to maintain my oral hygiene, and price lower than 50.00 dollars \n",
            "[Search] \n",
            "\n",
            "Action: search[3 ounce blue color toothbrushes for sensitive skin, it will help to maintain toothbrushes and will make your oral hygiene easy. Price: $25.00\n",
            "Review:\n",
            " [This Action]\n",
            " Action: buy\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            "\n",
            "\n",
            "[Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            "\n",
            "\n",
            "[Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action]\n",
            " [Action\n",
            "Observation: Invalid action!\n",
            "\n",
            "Action: look\n",
            "Action: look\n",
            "Action: look\n",
            "Action: look\n",
            "Action: look\n",
            "Action: look\n",
            "Action: look\n",
            "Action: look\n",
            "Action: look\n",
            "Action: look\n",
            "Action: go \n",
            "Action: go\n",
            "Action: go\n",
            "Action: go\n",
            "Action: go\n",
            "Action: go\n",
            "Action: go\n",
            "Action: go\n",
            "Action: go\n",
            "Action: go \n",
            "Action: go\n",
            "Action: go \n",
            "Observation: Invalid action!\n",
            "\n",
            "Action:\n"
          ]
        },
        {
          "ename": "IndexError",
          "evalue": "index out of range in self",
          "output_type": "error",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[1;32m/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb Cell 8\u001b[0m line \u001b[0;36m1\n\u001b[0;32m----> <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=0'>1</a>\u001b[0m res1 \u001b[39m=\u001b[39m run_episodes(prompt1, \u001b[39m1\u001b[39;49m)\n",
            "\u001b[1;32m/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb Cell 8\u001b[0m line \u001b[0;36m4\n\u001b[1;32m     <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=43'>44</a>\u001b[0m \u001b[39mprint\u001b[39m(i)\n\u001b[1;32m     <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=44'>45</a>\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m---> <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=45'>46</a>\u001b[0m   r \u001b[39m=\u001b[39m webshop_run(\u001b[39mf\u001b[39;49m\u001b[39m'\u001b[39;49m\u001b[39mfixed_\u001b[39;49m\u001b[39m{\u001b[39;49;00mi\u001b[39m}\u001b[39;49;00m\u001b[39m'\u001b[39;49m, prompt, to_print\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m)\n\u001b[1;32m     <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=46'>47</a>\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mAssertionError\u001b[39;00m:\n\u001b[1;32m     <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=47'>48</a>\u001b[0m   r \u001b[39m=\u001b[39m \u001b[39m0\u001b[39m\n",
            "\u001b[1;32m/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb Cell 8\u001b[0m line \u001b[0;36m3\n\u001b[1;32m     <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=29'>30</a>\u001b[0m \u001b[39m# print(\"input to llm!!!\")\u001b[39;00m\n\u001b[1;32m     <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=30'>31</a>\u001b[0m \u001b[39m# switch to llm2 for different llms and modify output processing format accordingly\u001b[39;00m\n\u001b[1;32m     <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=31'>32</a>\u001b[0m \u001b[39mprint\u001b[39m(\u001b[39m\"\u001b[39m\u001b[39m============================current prompt: \u001b[39m\u001b[39m\"\u001b[39m, init_prompt \u001b[39m+\u001b[39m prompt[\u001b[39m-\u001b[39m(\u001b[39m5600\u001b[39m\u001b[39m-\u001b[39m\u001b[39mlen\u001b[39m(init_prompt)):])\n\u001b[0;32m---> <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=32'>33</a>\u001b[0m action \u001b[39m=\u001b[39m llm3(init_prompt \u001b[39m+\u001b[39;49m prompt[\u001b[39m-\u001b[39;49m(\u001b[39m5600\u001b[39;49m\u001b[39m-\u001b[39;49m\u001b[39mlen\u001b[39;49m(init_prompt)):], stop\u001b[39m=\u001b[39;49m[\u001b[39m'\u001b[39;49m\u001b[39m\\n\u001b[39;49;00m\u001b[39m'\u001b[39;49m])\u001b[39m.\u001b[39mlstrip(\u001b[39m'\u001b[39m\u001b[39m \u001b[39m\u001b[39m'\u001b[39m)\n\u001b[1;32m     <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=33'>34</a>\u001b[0m \u001b[39m#print(\"======================================================llm output: \", action)\u001b[39;00m\n\u001b[1;32m     <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=34'>35</a>\u001b[0m \u001b[39mprint\u001b[39m(\u001b[39m\"\u001b[39m\u001b[39m============================================================================================================\u001b[39m\u001b[39m\"\u001b[39m)\n",
            "\u001b[1;32m/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb Cell 8\u001b[0m line \u001b[0;36m4\n\u001b[1;32m      <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=1'>2</a>\u001b[0m inputs \u001b[39m=\u001b[39m tokenizer(prompt, return_tensors\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mpt\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[1;32m      <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=2'>3</a>\u001b[0m \u001b[39m# print(\"input::::::::\", inputs, \"finished:::::::::::::\")\u001b[39;00m\n\u001b[0;32m----> <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=3'>4</a>\u001b[0m tokens \u001b[39m=\u001b[39m model\u001b[39m.\u001b[39;49mgenerate(\n\u001b[1;32m      <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=4'>5</a>\u001b[0m \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49minputs,\n\u001b[1;32m      <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=5'>6</a>\u001b[0m max_new_tokens\u001b[39m=\u001b[39;49m\u001b[39m256\u001b[39;49m,\n\u001b[1;32m      <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=6'>7</a>\u001b[0m do_sample\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m,\n\u001b[1;32m      <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=7'>8</a>\u001b[0m temperature\u001b[39m=\u001b[39;49m\u001b[39m1.0\u001b[39;49m,\n\u001b[1;32m      <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=8'>9</a>\u001b[0m top_p\u001b[39m=\u001b[39;49m\u001b[39m1.0\u001b[39;49m,\n\u001b[1;32m     <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=9'>10</a>\u001b[0m )\n\u001b[1;32m     <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=10'>11</a>\u001b[0m \u001b[39m# print(\"model output!!!!!!!!!!!!!!!!!!!!!!!!\", tokens, \"finished!!!!!!!!!!!!!!!!!!\")\u001b[39;00m\n\u001b[1;32m     <a href='vscode-notebook-cell://ssh-remote%2Bec2-54-158-100-186.compute-1.amazonaws.com/home/ubuntu/Ruiyu/11-777-MMML-Project/React.ipynb#X10sdnNjb2RlLXJlbW90ZQ%3D%3D?line=11'>12</a>\u001b[0m \u001b[39mreturn\u001b[39;00m tokenizer\u001b[39m.\u001b[39mdecode(tokens[\u001b[39m0\u001b[39m], skip_special_tokens\u001b[39m=\u001b[39m\u001b[39mTrue\u001b[39;00m)\n",
            "File \u001b[0;32m~/anaconda3/envs/webshop/lib/python3.8/site-packages/torch/utils/_contextlib.py:115\u001b[0m, in \u001b[0;36mcontext_decorator.<locals>.decorate_context\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    112\u001b[0m \u001b[39m@functools\u001b[39m\u001b[39m.\u001b[39mwraps(func)\n\u001b[1;32m    113\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mdecorate_context\u001b[39m(\u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs):\n\u001b[1;32m    114\u001b[0m     \u001b[39mwith\u001b[39;00m ctx_factory():\n\u001b[0;32m--> 115\u001b[0m         \u001b[39mreturn\u001b[39;00m func(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n",
            "File \u001b[0;32m~/anaconda3/envs/webshop/lib/python3.8/site-packages/transformers/generation_utils.py:1282\u001b[0m, in \u001b[0;36mGenerationMixin.generate\u001b[0;34m(self, inputs, max_length, min_length, do_sample, early_stopping, num_beams, temperature, top_k, top_p, typical_p, repetition_penalty, bad_words_ids, force_words_ids, bos_token_id, pad_token_id, eos_token_id, length_penalty, no_repeat_ngram_size, encoder_no_repeat_ngram_size, num_return_sequences, max_time, max_new_tokens, decoder_start_token_id, use_cache, num_beam_groups, diversity_penalty, prefix_allowed_tokens_fn, logits_processor, stopping_criteria, constraints, output_attentions, output_hidden_states, output_scores, return_dict_in_generate, forced_bos_token_id, forced_eos_token_id, remove_invalid_values, synced_gpus, exponential_decay_length_penalty, **model_kwargs)\u001b[0m\n\u001b[1;32m   1274\u001b[0m     input_ids, model_kwargs \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_expand_inputs_for_generation(\n\u001b[1;32m   1275\u001b[0m         input_ids,\n\u001b[1;32m   1276\u001b[0m         expand_size\u001b[39m=\u001b[39mnum_return_sequences,\n\u001b[1;32m   1277\u001b[0m         is_encoder_decoder\u001b[39m=\u001b[39m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mconfig\u001b[39m.\u001b[39mis_encoder_decoder,\n\u001b[1;32m   1278\u001b[0m         \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mmodel_kwargs,\n\u001b[1;32m   1279\u001b[0m     )\n\u001b[1;32m   1281\u001b[0m     \u001b[39m# 12. run sample\u001b[39;00m\n\u001b[0;32m-> 1282\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49msample(\n\u001b[1;32m   1283\u001b[0m         input_ids,\n\u001b[1;32m   1284\u001b[0m         logits_processor\u001b[39m=\u001b[39;49mlogits_processor,\n\u001b[1;32m   1285\u001b[0m         logits_warper\u001b[39m=\u001b[39;49mlogits_warper,\n\u001b[1;32m   1286\u001b[0m         stopping_criteria\u001b[39m=\u001b[39;49mstopping_criteria,\n\u001b[1;32m   1287\u001b[0m         pad_token_id\u001b[39m=\u001b[39;49mpad_token_id,\n\u001b[1;32m   1288\u001b[0m         eos_token_id\u001b[39m=\u001b[39;49meos_token_id,\n\u001b[1;32m   1289\u001b[0m         output_scores\u001b[39m=\u001b[39;49moutput_scores,\n\u001b[1;32m   1290\u001b[0m         return_dict_in_generate\u001b[39m=\u001b[39;49mreturn_dict_in_generate,\n\u001b[1;32m   1291\u001b[0m         synced_gpus\u001b[39m=\u001b[39;49msynced_gpus,\n\u001b[1;32m   1292\u001b[0m         \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mmodel_kwargs,\n\u001b[1;32m   1293\u001b[0m     )\n\u001b[1;32m   1295\u001b[0m \u001b[39melif\u001b[39;00m is_beam_gen_mode:\n\u001b[1;32m   1296\u001b[0m     \u001b[39mif\u001b[39;00m num_return_sequences \u001b[39m>\u001b[39m num_beams:\n",
            "File \u001b[0;32m~/anaconda3/envs/webshop/lib/python3.8/site-packages/transformers/generation_utils.py:1893\u001b[0m, in \u001b[0;36mGenerationMixin.sample\u001b[0;34m(self, input_ids, logits_processor, stopping_criteria, logits_warper, max_length, pad_token_id, eos_token_id, output_attentions, output_hidden_states, output_scores, return_dict_in_generate, synced_gpus, **model_kwargs)\u001b[0m\n\u001b[1;32m   1890\u001b[0m model_inputs \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mprepare_inputs_for_generation(input_ids, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mmodel_kwargs)\n\u001b[1;32m   1892\u001b[0m \u001b[39m# forward pass to get next token\u001b[39;00m\n\u001b[0;32m-> 1893\u001b[0m outputs \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m(\n\u001b[1;32m   1894\u001b[0m     \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mmodel_inputs,\n\u001b[1;32m   1895\u001b[0m     return_dict\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m,\n\u001b[1;32m   1896\u001b[0m     output_attentions\u001b[39m=\u001b[39;49moutput_attentions,\n\u001b[1;32m   1897\u001b[0m     output_hidden_states\u001b[39m=\u001b[39;49moutput_hidden_states,\n\u001b[1;32m   1898\u001b[0m )\n\u001b[1;32m   1900\u001b[0m \u001b[39mif\u001b[39;00m synced_gpus \u001b[39mand\u001b[39;00m this_peer_finished:\n\u001b[1;32m   1901\u001b[0m     cur_len \u001b[39m=\u001b[39m cur_len \u001b[39m+\u001b[39m \u001b[39m1\u001b[39m\n",
            "File \u001b[0;32m~/anaconda3/envs/webshop/lib/python3.8/site-packages/torch/nn/modules/module.py:1518\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1516\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_compiled_call_impl(\u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)  \u001b[39m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m   1517\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m-> 1518\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_call_impl(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n",
            "File \u001b[0;32m~/anaconda3/envs/webshop/lib/python3.8/site-packages/torch/nn/modules/module.py:1527\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1522\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1523\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1524\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_pre_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m   1525\u001b[0m         \u001b[39mor\u001b[39;00m _global_backward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1526\u001b[0m         \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1527\u001b[0m     \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m   1529\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m   1530\u001b[0m     result \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m\n",
            "File \u001b[0;32m~/anaconda3/envs/webshop/lib/python3.8/site-packages/transformers/models/gpt2/modeling_gpt2.py:1047\u001b[0m, in \u001b[0;36mGPT2LMHeadModel.forward\u001b[0;34m(self, input_ids, past_key_values, attention_mask, token_type_ids, position_ids, head_mask, inputs_embeds, encoder_hidden_states, encoder_attention_mask, labels, use_cache, output_attentions, output_hidden_states, return_dict)\u001b[0m\n\u001b[1;32m   1039\u001b[0m \u001b[39m\u001b[39m\u001b[39mr\u001b[39m\u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m   1040\u001b[0m \u001b[39mlabels (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*):\u001b[39;00m\n\u001b[1;32m   1041\u001b[0m \u001b[39m    Labels for language modeling. Note that the labels **are shifted** inside the model, i.e. you can set\u001b[39;00m\n\u001b[1;32m   1042\u001b[0m \u001b[39m    `labels = input_ids` Indices are selected in `[-100, 0, ..., config.vocab_size]` All labels set to `-100`\u001b[39;00m\n\u001b[1;32m   1043\u001b[0m \u001b[39m    are ignored (masked), the loss is only computed for labels in `[0, ..., config.vocab_size]`\u001b[39;00m\n\u001b[1;32m   1044\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m   1045\u001b[0m return_dict \u001b[39m=\u001b[39m return_dict \u001b[39mif\u001b[39;00m return_dict \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39melse\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mconfig\u001b[39m.\u001b[39muse_return_dict\n\u001b[0;32m-> 1047\u001b[0m transformer_outputs \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mtransformer(\n\u001b[1;32m   1048\u001b[0m     input_ids,\n\u001b[1;32m   1049\u001b[0m     past_key_values\u001b[39m=\u001b[39;49mpast_key_values,\n\u001b[1;32m   1050\u001b[0m     attention_mask\u001b[39m=\u001b[39;49mattention_mask,\n\u001b[1;32m   1051\u001b[0m     token_type_ids\u001b[39m=\u001b[39;49mtoken_type_ids,\n\u001b[1;32m   1052\u001b[0m     position_ids\u001b[39m=\u001b[39;49mposition_ids,\n\u001b[1;32m   1053\u001b[0m     head_mask\u001b[39m=\u001b[39;49mhead_mask,\n\u001b[1;32m   1054\u001b[0m     inputs_embeds\u001b[39m=\u001b[39;49minputs_embeds,\n\u001b[1;32m   1055\u001b[0m     encoder_hidden_states\u001b[39m=\u001b[39;49mencoder_hidden_states,\n\u001b[1;32m   1056\u001b[0m     encoder_attention_mask\u001b[39m=\u001b[39;49mencoder_attention_mask,\n\u001b[1;32m   1057\u001b[0m     use_cache\u001b[39m=\u001b[39;49muse_cache,\n\u001b[1;32m   1058\u001b[0m     output_attentions\u001b[39m=\u001b[39;49moutput_attentions,\n\u001b[1;32m   1059\u001b[0m     output_hidden_states\u001b[39m=\u001b[39;49moutput_hidden_states,\n\u001b[1;32m   1060\u001b[0m     return_dict\u001b[39m=\u001b[39;49mreturn_dict,\n\u001b[1;32m   1061\u001b[0m )\n\u001b[1;32m   1062\u001b[0m hidden_states \u001b[39m=\u001b[39m transformer_outputs[\u001b[39m0\u001b[39m]\n\u001b[1;32m   1064\u001b[0m \u001b[39m# Set device for model parallelism\u001b[39;00m\n",
            "File \u001b[0;32m~/anaconda3/envs/webshop/lib/python3.8/site-packages/torch/nn/modules/module.py:1518\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1516\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_compiled_call_impl(\u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)  \u001b[39m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m   1517\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m-> 1518\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_call_impl(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n",
            "File \u001b[0;32m~/anaconda3/envs/webshop/lib/python3.8/site-packages/torch/nn/modules/module.py:1527\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1522\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1523\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1524\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_pre_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m   1525\u001b[0m         \u001b[39mor\u001b[39;00m _global_backward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1526\u001b[0m         \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1527\u001b[0m     \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m   1529\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m   1530\u001b[0m     result \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m\n",
            "File \u001b[0;32m~/anaconda3/envs/webshop/lib/python3.8/site-packages/transformers/models/gpt2/modeling_gpt2.py:834\u001b[0m, in \u001b[0;36mGPT2Model.forward\u001b[0;34m(self, input_ids, past_key_values, attention_mask, token_type_ids, position_ids, head_mask, inputs_embeds, encoder_hidden_states, encoder_attention_mask, use_cache, output_attentions, output_hidden_states, return_dict)\u001b[0m\n\u001b[1;32m    832\u001b[0m \u001b[39mif\u001b[39;00m inputs_embeds \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m    833\u001b[0m     inputs_embeds \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mwte(input_ids)\n\u001b[0;32m--> 834\u001b[0m position_embeds \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mwpe(position_ids)\n\u001b[1;32m    835\u001b[0m hidden_states \u001b[39m=\u001b[39m inputs_embeds \u001b[39m+\u001b[39m position_embeds\n\u001b[1;32m    837\u001b[0m \u001b[39mif\u001b[39;00m token_type_ids \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n",
            "File \u001b[0;32m~/anaconda3/envs/webshop/lib/python3.8/site-packages/torch/nn/modules/module.py:1518\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1516\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_compiled_call_impl(\u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)  \u001b[39m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m   1517\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m-> 1518\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_call_impl(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n",
            "File \u001b[0;32m~/anaconda3/envs/webshop/lib/python3.8/site-packages/torch/nn/modules/module.py:1527\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1522\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1523\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1524\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_pre_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m   1525\u001b[0m         \u001b[39mor\u001b[39;00m _global_backward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1526\u001b[0m         \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1527\u001b[0m     \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m   1529\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m   1530\u001b[0m     result \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m\n",
            "File \u001b[0;32m~/anaconda3/envs/webshop/lib/python3.8/site-packages/torch/nn/modules/sparse.py:162\u001b[0m, in \u001b[0;36mEmbedding.forward\u001b[0;34m(self, input)\u001b[0m\n\u001b[1;32m    161\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mforward\u001b[39m(\u001b[39mself\u001b[39m, \u001b[39minput\u001b[39m: Tensor) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m Tensor:\n\u001b[0;32m--> 162\u001b[0m     \u001b[39mreturn\u001b[39;00m F\u001b[39m.\u001b[39;49membedding(\n\u001b[1;32m    163\u001b[0m         \u001b[39minput\u001b[39;49m, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mweight, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mpadding_idx, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mmax_norm,\n\u001b[1;32m    164\u001b[0m         \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mnorm_type, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mscale_grad_by_freq, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49msparse)\n",
            "File \u001b[0;32m~/anaconda3/envs/webshop/lib/python3.8/site-packages/torch/nn/functional.py:2233\u001b[0m, in \u001b[0;36membedding\u001b[0;34m(input, weight, padding_idx, max_norm, norm_type, scale_grad_by_freq, sparse)\u001b[0m\n\u001b[1;32m   2227\u001b[0m     \u001b[39m# Note [embedding_renorm set_grad_enabled]\u001b[39;00m\n\u001b[1;32m   2228\u001b[0m     \u001b[39m# XXX: equivalent to\u001b[39;00m\n\u001b[1;32m   2229\u001b[0m     \u001b[39m# with torch.no_grad():\u001b[39;00m\n\u001b[1;32m   2230\u001b[0m     \u001b[39m#   torch.embedding_renorm_\u001b[39;00m\n\u001b[1;32m   2231\u001b[0m     \u001b[39m# remove once script supports set_grad_enabled\u001b[39;00m\n\u001b[1;32m   2232\u001b[0m     _no_grad_embedding_renorm_(weight, \u001b[39minput\u001b[39m, max_norm, norm_type)\n\u001b[0;32m-> 2233\u001b[0m \u001b[39mreturn\u001b[39;00m torch\u001b[39m.\u001b[39;49membedding(weight, \u001b[39minput\u001b[39;49m, padding_idx, scale_grad_by_freq, sparse)\n",
            "\u001b[0;31mIndexError\u001b[0m: index out of range in self"
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